Spectrum Sensing Using Empirical Mode Decomposition and Relative Entropy

Recently, as many new wireless services emerge, number of the users needing to access the limited frequency spectrum is increased. This brings the need for improvements on efficient spectrum utilization. Cognitive Radio (CR) is proposed as a solution to this problem. Spectrum sensing is an essential component of CR to increase spectrum usage efficiency. One of the most important problems encountered in spectrum sensing is the noise uncertainty of the channel. In this study, an Empirical Mode Decomposition (EMD) based spectrum sensing algorithm using relative entropy is proposed. This approach is shown to be robust to noise uncertainty and provide promising probability of detection results by using computer simulations.